Guided Learning for Bidirectional Sequence Classification

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• Yue Zhang ()
• Thursday 10 February 2011, 12:00-13:00
• GS15, Computer Laboratory.

If you have a question about this talk, please contact Jimme Jardine.

This week Yue will be talking about:

Guided Learning for Bidirectional Sequence Classification http://www.aclweb.org/anthology-new/P/P07/P07-1096.pdf

In this paper, we propose guided learning, a new learning framework for bidirectional sequence classification. The tasks of learning the order of inference and training the local classifier are dynamically incorporated into a single Perceptron like learning algorithm. We apply this novel learning algorithm to POS tagging. It obtains an error rate of 2.67% on the standard PTB test set, which represents 3.3% relative error reduction over the previous best result on the same data set, while using fewer features.

This talk is part of the Natural Language Processing Reading Group series.

This talk is included in these lists:

• Cambridge Forum of Science and Humanities
• Cambridge Language Sciences
• Cambridge talks
• Chris Davis' list
• GS15, Computer Laboratory
• Guy Emerson's list
• Natural Language Processing Reading Group

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